Quality Assurance Specialist

Aislelabs•Oakville, ON

19d•Remote

About The Position

The Quality Assurance Specialist is a critical individual contributor within the Aislelabs Engineering division, responsible for end-to-end platform quality across all products and modules, including the Flow, Connect, and Marketing suites. This role spans the full spectrum of QA disciplines—test strategy, test execution, automation, defect lifecycle management, and release validation—requiring both strategic thinking and strong hands-on delivery. The Quality Assurance Specialist works closely with Engineering, Product Management, and DevOps to embed quality throughout the development lifecycle, serving as a primary voice of quality standards and risk assessment at every release. The ideal candidate is highly adaptable across testing disciplines, self-directed, and motivated by building quality practices that scale with a growing SaaS platform. Experience leveraging AI tools to enhance test coverage and efficiency is highly valued.

Requirements

3+ years of experience in a software QA role with ownership of test planning, execution, defect management, and release validation within a SaaS or software product environment.
Experience operating as a generalist QA resource across multiple products or modules simultaneously, independently managing scope, priority, and risk across a broad and varied testing workload.
Solid understanding of software testing methodologies including functional, regression, integration, exploratory, boundary, and performance testing.
Hands-on experience with API testing tools (e.g., Postman) and at least one test automation framework (e.g., Selenium, Playwright, Cypress, or equivalent).
Working knowledge of Jira for defect logging, sprint participation, and QA estimation; familiarity with agile/scrum development processes.
Ability to write clear, detailed, reproducible test cases and defect reports; basic proficiency in SQL or query tools for data validation.
Strong analytical, communication, and documentation skills; highly organized, self-directed, and effective in a fully remote environment.
Demonstrated ability to use large language models (such as Claude, ChatGPT, or similar) to generate test cases, create test data, draft defect reports, produce QA documentation, and analyze test results—integrating AI meaningfully into day-to-day QA workflows.

Nice To Haves

Experience using AI-powered testing tools (such as Testim, Mabl, Applitools, or similar) to accelerate test creation, improve coverage, and reduce manual testing effort through intelligent test generation and self-healing automation.
Familiarity with prompt engineering techniques for QA use cases, including generating edge case scenarios, boundary condition tests, and regression scripts from feature specifications or user stories.
Experience using AI tools to analyze defect patterns, identify recurring root causes, and surface quality trends from historical test and issue data.
Working knowledge of performance and load testing tools (e.g., JMeter, Gatling, k6); experience with CI/CD pipeline integration (e.g., Jenkins, GitHub Actions) for automated test gating.
Experience testing platforms with spatial data, real-time event processing, large-scale data ingestion, or IoT/hardware-connected architectures.
Familiarity with cloud infrastructure concepts (e.g., AWS), accessibility testing standards (WCAG), and security testing fundamentals (OWASP Top 10).
Working knowledge of DevOps tools including Confluence, version control (Git), and experience collaborating within international engineering teams across multiple time zones.
Highly motivated self-starter with intellectual curiosity, a passion for software quality, and the resilience to maintain high standards in a fast-paced environment.
High proficiency with Microsoft Office.

Responsibilities

Own and continuously evolve the QA strategy across all platform products and modules, including the approach to functional, regression, integration, performance, and release validation testing.
Develop and maintain test plans for each release cycle covering scope, risk areas, test types, and entry/exit criteria, in alignment with Engineering release schedules and sprint planning.
Define and maintain QA standards, documentation practices, and testing methodologies that provide consistency and repeatability; maintain a prioritized test coverage map across the full platform.
Participate actively in sprint ceremonies—planning, grooming, stand-ups, and retrospectives—contributing QA estimates, surfacing quality risks early, and providing data-driven improvement recommendations.
Design, author, and maintain a comprehensive library of test cases covering functional, regression, integration, boundary, edge case, and exploratory scenarios across all platform modules and workflows.
Execute thorough functional and regression testing of new features, enhancements, and bug fixes prior to each release, validating against approved requirements, acceptance criteria, and design specifications.
Perform API-level testing using tools such as Postman or equivalent, verifying endpoint behavior, request/response payloads, authentication, error handling, and integration data flows end to end.
Validate UI/UX implementations across supported browsers, operating systems, and device types, and test end-to-end workflows spanning multiple platform modules and services.
Design and execute performance and load tests to validate platform scalability and stability under realistic and peak conditions, defining benchmarks and identifying bottlenecks in collaboration with Engineering.
Develop, maintain, and expand an automated test suite using appropriate frameworks aligned to the platform stack (Java, JavaScript/TypeScript, React), integrated into the CI/CD pipeline where applicable.
Continuously review and refactor automated scripts to maintain reliability and keep pace with platform changes; prioritize automation candidates based on frequency, execution time, and regression risk.
Log all defects completely in Jira with reproducible steps, environment details, severity/priority classifications, and supporting evidence; manage the full defect lifecycle from discovery through fix verification.
Triage and prioritize defect queues in collaboration with Engineering and Product, communicating release-blocking risk clearly and maintaining defect trend and root cause analysis records.
Own the release readiness assessment, providing a go/no-go recommendation with supporting sign-off documentation summarizing test scope, results, known issues, and accepted risk for each production release.
Establish, document, and continuously refine QA processes, standards, and workflows; build and maintain reusable assets including test plans, checklists, and environment configurations.
Act as the internal advocate for software quality, engaging Engineering and Product teams in shared accountability for platform excellence and contributing structured feedback to improve release predictability.
Contribute to knowledge base documentation and support the broader team with QA insight on escalated customer-reported issues and platform defect investigations as required.